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Marc Brooker

AI is transforming systems research by automating performance optimization through reliable verifiers, but this shift creates a critical bottleneck: choosing the right problems to solve. While AI excels at hill climbing and making numbers bigger, the real challenge lies in selecting meaningful problems and formulating them precisely. The future quality of systems research depends on whether the community focuses on insightful problem selection or produces higher volumes of meaningless optimization. Testing and verification will become increasingly important as AI takes over solution discovery.

Is Systems Research Really Just About Making Numbers Bigger?